Demography最新文献

The racial and ethnic diversification of the U.S. population has transformed the demographic makeup of communities and rapidly increased exposure to diversity in American neighborhoods. Although diversity exposure occurs throughout people's daily lives, the conventional approach to describing diversity only at places of residence potentially understates the full extent of this phenomenon. In this study, we explore short-term, within-day changes in the diversity of different neighborhoods by considering U.S. workers' work and residential locations. Using estimates for daytime and nighttime populations among metropolitan census tracts, our empirical analyses investigate the extent to which the process of daytime mobility for work relates to changes in the racial and ethnic diversity of different spaces. Our results indicate widespread daily shifts toward diversity for most neighborhood types, especially those with residential (nighttime) populations that are predominantly Black, Latino, or Asian. We find that patterns of intraday diversification experienced minor declines across recent decades but are present in most metropolitan areas. Our findings also show that intraday changes in racial and ethnic diversity overlap with nonracial forms of daily diversity change. Further, average within-day changes in diversity are more pronounced in areas with greater residential segregation.

Despite recent economic growth and reductions in child mortality in many African countries, the region has experienced a slow fertility transition. In this study, we explore whether the slow structural economic change on the continent can explain this discrepancy. We construct a unique panel dataset combining Demographic and Health Surveys and nighttime light intensity data (an indicator of industrialization) from 57 countries at the subnational region level over three decades to analyze the drivers of fertility transitions across low- and middle-income countries. Our results confirm that household wealth, reduced child mortality, and female primary education are crucial for fertility declines. However, our analysis also highlights the importance of indicators of structural economic change, including the share of labor in nonagricultural occupations, industrialization, the share of women with higher education, and the formalization of the economy. Our simulations suggest that if high-fertility countries in sub-Saharan Africa underwent structural economic transformations comparable to those of other low- and middle-income countries with low fertility rates, their fertility levels could fall by 1 to 1.6 children.

The transgender population is a critically underresearched population in the United States, owing to rare measures on national and state-level surveys that ask about sex and gender or transgender identification. Consequently, we know relatively less about the sociodemographic, socioeconomic, family, and health lives of gender minorities. In this research note, I use population-level data from the Centers for Disease Control and Prevention's Behavioral Risk Factor Surveillance System to provide a data portrait of cisgender, transgender, and gender-nonconforming populations on a range of sociodemographic (e.g., sexual identity, race and ethnicity), socioeconomic (e.g., education, homeownership), family (e.g., union status), and health (e.g., number of poor mental health days) characteristics. Results reveal that gender minorities are younger than cisgender men and cisgender women and are disproportionately sexual minorities and people of color. Gender minority groups also experience lower socioeconomic status, report drastically different family lives, and bear the burden of worse health compared with cisgender people. I conclude by contending that descriptive research of this nature can illuminate compositional differences between cisgender and gender minority populations, provide rationales for adjusting for certain characteristics, and highlight potential explanatory mechanisms to make better sense of well-established findings (e.g., the transgender health disadvantage).